performance-pass

Identify performance regressions by profiling latency, throughput, memory, and database load.

Updated Feb 18, 2026

Search Tags:#performance #benchmarking #profiling #regression #latency #throughput #code-review

Ready to run

npx skills add https://github.com/askaret/codex-skills --skill performance-pass

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: performance-pass
Source: https://github.com/askaret/codex-skills/tree/main/.agents/skills/performance-pass
Command: npx skills add https://github.com/askaret/codex-skills --skill performance-pass

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps teams quickly identify and prevent performance regressions by surfacing obvious bottlenecks in latency, throughput, rendering, memory, or database load.

Core Features & Use Cases

Backend checks for API performance, including pagination defaults, avoiding N+1 patterns, adding appropriate caching headers, and validating payload sizes.
Database considerations such as index alignment with query predicates and sort order, migration impact, and monitoring for inefficient queries.
Runtime and frontend considerations like minimizing allocations in hot paths, ensuring correct async usage, and safe data-fetching and rendering strategies.
Verification steps include running builds, collecting metrics, comparing baselines, and documenting potential perf risks and mitigations.

Quick Start

Run a quick performance audit on the affected feature and capture baseline latency and memory metrics.

Frequently Asked Questions about performance-pass

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I prevent performance regressions before deploying code changes?▼

Prevent performance regressions by profiling affected features, collecting baseline metrics for latency and memory, and running non-invasive checks with clear pass/fail criteria before release.

What is the best way to spot backend API bottlenecks like N+1 query patterns?▼

Spot backend API bottlenecks by reviewing pagination defaults, validating payload sizes, adding appropriate caching headers, and verifying database index alignment with query predicates and sort orders.

How does profiling memory allocations in hot paths improve throughput?▼

Profiling memory allocations in hot paths improves throughput by minimizing unnecessary object creation, ensuring correct async usage, and validating safe data-fetching and rendering strategies.

What database performance checks should I run when applying migrations?▼

When applying database migrations, check index alignment with query predicates and sort orders, monitor for inefficient queries, and validate the migration's overall impact on database load.

Can I use this approach to audit both frontend rendering and backend latency?▼

Yes, you can audit both frontend rendering and backend latency by applying non-invasive checks that monitor rendering strategies, API payload sizes, and memory allocations across the full stack.